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用于流式细胞术细胞周期分析的葡萄休眠腋芽细胞核制备方法的评估

An Evaluation of Nuclei Preparation of the Dormant Axillary Bud of Grapevine for Cell Cycle Analysis by Flow Cytometry.

作者信息

Hermawaty Dina, Considine John A, Considine Michael J

机构信息

UWA School of Agriculture and Environment, The UWA Institute of Agriculture, The University of Western Australia, Perth, WA, Australia.

ARC Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, WA, Australia.

出版信息

Front Plant Sci. 2022 Feb 24;13:834977. doi: 10.3389/fpls.2022.834977. eCollection 2022.

Abstract

Whether the division of cells of a dormant meristem may be arrested, e.g., in the G1 phase, has proven to be an extremely difficult hypothesis to test. This is particularly so for woody perennial buds, where dormant and quiescent states are diffuse, and the organ may remain visibly unchanged for 6-9 months of the year. Flow cytometry (FCM) has been widely applied in plant studies to determine the genome size and endopolyploidy. In this study, we present the application of FCM to measure the cell cycle status in mature dormant buds of grapevine ( cv. Cabernet Sauvignon), which represent a technically recalcitrant structure. This protocol illustrates the optimisation and validation of FCM data analysis to calculate the cell cycle status, or mitotic index, of dormant grapevine buds. We have shown how contamination with debris can be experimentally managed and give reference to the more malleable tomato leaves. We have also given a clear illustration of the primary pitfalls of data analysis to avoid artefacts or false results. Data acquisition and analysis strategies are detailed and can be readily applied to analyse FCM data from other recalcitrant plant samples.

摘要

休眠分生组织的细胞分裂是否会停滞,例如在G1期,已被证明是一个极难验证的假说。对于木本多年生芽来说尤其如此,其休眠和静止状态并不明确,而且该器官在一年中的6至9个月可能看起来没有明显变化。流式细胞术(FCM)已广泛应用于植物研究,以确定基因组大小和核内多倍性。在本研究中,我们展示了如何应用FCM来测量葡萄(赤霞珠品种)成熟休眠芽中的细胞周期状态,这是一种技术上难以处理的结构。本方案阐述了FCM数据分析的优化和验证,以计算休眠葡萄芽的细胞周期状态或有丝分裂指数。我们展示了如何通过实验处理碎片污染问题,并以更易处理的番茄叶片作为参考。我们还清晰地说明了数据分析中的主要陷阱,以避免出现人为因素或错误结果。详细介绍了数据采集和分析策略,这些策略可直接应用于分析来自其他难处理植物样本的FCM数据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2d0d/8913039/332e167bcfdb/fpls-13-834977-g001.jpg

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